Medicine & Science in Sports & Exercise:
Neuromuscular Dysfunction in Diabetes: Role of Nerve Impairment and Training Status
SCOTTO SACCHETTI, MASSIMO1; BALDUCCI, STEFANO2,3; BAZZUCCHI, ILENIA1; CARLUCCI, FLAMINIA1; DI PALUMBO, ALESSANDRO SCOTTO1; HAXHI, JONIDA1; CONTI, FRANCESCO2; DI BIASE, NICOLINA4; CALANDRIELLO, EUGENIO5; PUGLIESE, GIUSEPPE2
1Department of Human Movement and Sport Sciences, “Foro Italico” University, Rome, ITALY; 2Department of Clinical and Molecular Medicine, “La Sapienza” University, and Diabetes Unit, Sant’ Andrea Hospital, Rome, ITALY; 3Metabolic Fitness Association, Monterotondo, Rome, ITALY; 4Diabetes Unit, Fatebenefratelli San Pietro Hospital, Rome, ITALY; and 5Neurology and Neuro-Pathophysiology Unit, Regina Apostolorum Hospital, Albano, Rome, ITALY
Address for correspondence: Massimo Sacchetti, Ph.D., Department of Human Movement and Sports Sciences, “Foro Italico” University, Piazza Lauro De Bosis, 15-00135 Rome, Italy; E-mail: email@example.com.
Submitted for publication May 2012.
Accepted for publication July 2012.
Purpose: The purpose of this study was to investigate the effect of diabetes, motor nerve impairment, and training status on neuromuscular function by concurrent assessment of the torque–velocity relationship and muscle fiber conduction velocity (MFCV).
Methods: Four groups were studied (n = 12 each): sedentary patients with diabetes in the first (lower) and fourth (higher) quartile of motor nerve conduction velocity (D1 and D4, respectively), trained diabetic (TD) patients, and nondiabetic sedentary control (C) subjects. Maximal isometric and isokinetic contractions were assessed over a wide range of angular velocities for the elbow flexors and knee extensors to evaluate the torque–velocity relationship. Simultaneously, MFCV was estimated from surface electromyography of the vastus lateralis and biceps brachii.
Results: Isometric strength was similar among groups. The dynamic strength of elbow flexors was reduced in patients with diabetes at the higher contraction speeds. The strength of knee extensors was lower in sedentary patients with diabetes at all velocities considered, with significantly lower values in D1 than that in D4 at 60°, 90°, and 120°·s−1, whereas it was similar between TD and C subjects, especially at low contraction velocities. At the vastus lateralis, but not the biceps brachii, MFCV was lower in D1 and D4 as compared with TD and C subjects, showing similar values.
Conclusions: Muscle weakness in diabetes affects also the upper limb, although to a lower extent than the lower limb, is only partly related to motor nerve impairment, and is dependent on contraction velocity. Exercise training might counteract diabetes-induced alterations in muscle fiber contractile properties and MFCV.
Patients with diabetes are at high risk of developing physical disabilities after the age of 60 yr as compared with nondiabetic subjects (19). Muscle weakness, which has been reported in subjects with both type 1 (2) and type 2 (1) diabetes, may contribute to this association (22). Reduced muscle strength was shown to be associated with decreased muscle mass (5) and quality (30), that is, muscle strength per unit of regional muscle mass. Muscle weakness and atrophy in diabetes affect the distal segments of the lower limbs, thus mimicking the distribution of diabetic polyneuropathy (DPN) (1,2,5,30). In fact, several reports have shown a relationship between reduced muscle isokinetic strength and presence and severity of peripheral nerve dysfunction (1,2,5), thus suggesting that muscle weakness is a late complication of DPN with motor nerve impairment (4). In diabetic subjects, exercise training has been shown to provide multiple benefits (39), including improvements in muscle strength and function (16) and also a counteracting effect on DPN progression (6). However, recent studies have shown that lower leg isometric strength was reduced in individuals with type 2 diabetes as compared with control subjects, independent of DPN (21,22). This is consistent with other reports showing that impairment of muscle strength occurs earlier in the course of diabetes (34) and also affects the upper limbs (29), with diabetes being one of the factors associated with accelerated handgrip weakness with aging (35). Thus, in addition to DPN, other factors have been claimed to explain the reduction of muscle strength in diabetes, including alterations of either whole muscle or single-fiber contractile properties (11,17,24,33) and changes in fiber type distribution (18,28). All these modifications may influence joint power in a manner that diminishes the performance of activities of daily living.
The torque–angular velocity relationship provides important information on the contractile pattern of a muscle acting on a joint. A calculation of this relationship from measurements of isometric and isokinetic concentric maximal voluntary contractions (MVCs) may provide a proper characterization of the derangement of neuromuscular function in diabetes, the role of motor nerve impairment, and the potential of exercise in restoring it. Indeed, the torque–velocity relationship provides information on the determinants of muscular power and reflects the fundamental mechanisms responsible for force generation (10). Moreover, from a practical perspective, the consideration of force–velocity interactions is relevant for understanding the performance during functional tasks, as shown in older individuals (34). Unfortunately, studies investigating muscle strength in diabetes have considered only single contraction speeds (1,2,4,5).
In addition to the contractile dysfunction associated with diabetes, studies in diabetic rodents have reported defects in sarcolemmal properties (20,25). The propagation velocity of the action potential along the muscle fiber (muscle fiber conduction velocity [MFCV]) is one of the physiological characteristics of the sarcolemma. Indeed, MFCV, which can be studied noninvasively by surface EMG (sEMG) (27), is directly related to sarcolemmal excitability/function and reflects muscle fiber type and size as well as pH (40). Therefore, it can provide useful information on motor unit recruitment strategies, peripheral fatigue, muscle atrophy, and defects in skeletal muscle sarcolemma. Although MFCV has been used to characterize several neuromuscular disorders (40), very few studies have been conducted in patients with diabetes. These studies, which examined the tibialis anterior muscle under electrically elicited contractions using invasive techniques, revealed a reduction of MFCV in neuropathic patients with diabetes (14,26).
In this study, we applied the assessment of the torque–velocity relationship and MFCV to investigate the effect of diabetes, motor nerve impairment, and training status on neuromuscular function of the upper and lower limb during both isometric and dynamic contractions. We hypothesize that strength deficit with diabetes and the effect of motor nerve impairment are related to contraction speed and to a reduced MFCV and that exercise training may counteract the impairment of neuromuscular function induced by the disease.
Patients with diabetes participating in this study were randomly selected from a cohort of 700 individuals, 140 with type 1 and 560 with type 2 diabetes, regularly followed up in an outpatient diabetes clinic and evaluated for the presence of somatic and autonomic neuropathy as described in the next section. The following groups were studied (n = 12 patients each): sedentary patients with diabetes, asymptomatic for DPN, from the first (lower) quartile (D1, 4 patients with type 1 diabetes) and the fourth (higher) quartile (D4, 4 patients with type 1 diabetes) of motor nerve conduction velocity (MNCV), and trained diabetic (TD) individuals (2 patients with type 1 diabetes). The training program for the TD group consisted of 150 min·wk−1 in two supervised sessions of progressive mixed (aerobic and resistance) exercise. The median number of sessions was 490 (interquartile range, 472–650) for a period of at least 4 yr. Aerobic training primarily involved the lower extremities and was performed using treadmill or cycle ergometer. Resistance training consisted of five exercises, that is, chest press, elbow flexions (arm curl), lateral pull down, knee extensions, and leg press. Nondiabetic sedentary subjects, who had also undergone neurological examination to exclude the presence of any neuropathy, served as controls (C; n = 12). Inclusion criteria were male sex and the ability to walk a 1.6-km distance without assistance, which was preliminarily tested under heart rate monitoring. Patients having any condition limiting or contraindicating exercise were excluded.
Subjects underwent measurement of clinical and biochemical parameters before the assessment of neuromuscular function. Group assignment was unknown to the examiners during execution of mechanical and electrophysiological tests. The research protocol was approved by the locally appointed ethics committee and participants gave written informed consent.
The whole diabetic cohort was carefully examined by a neurologist for the presence of somatic and/or autonomic DPN. The distal latencies and nerve conduction velocities of the peroneal motor and sural sensory nerves were measured bilaterally, together with the vibration perception threshold (VPT) in the left and right malleolus and hallux (7). Cardiovascular autonomic function was assessed by heart rate response to deep breathing, cough test, and standing as well as systolic blood pressure response to standing.
As stated earlier, patients with diabetes were divided into quartiles of peroneal MNCV, then D1 and D4 participants were randomly selected among men with sedentary habits to better discriminate the effect of motor nerve impairment, whereas TD participants were selected among patients previously engaged in the supervised training program. Also nondiabetic sedentary controls underwent neurological examination to exclude the presence of any neuropathy.
Clinical and Biochemical Parameters
Weight and height were measured while the participants were fasting and wearing only their undergarments, and body mass index was then calculated as body weight divided by height squared. Waist circumference was measured as the minimum circumference between the lower rib margin and the iliac crest while participants were standing with their heels together. Blood pressure was measured with a mercury sphygmomanometer on the right arm after at least 5 min of rest.
Fat mass and free fat mass measurements were performed using a whole body densitometer (QDR 2000plus; HologicItaly, Rome, Italy). Maximal oxygen consumption (V˙O2max) was assessed at the treadmill, using a modified Balke and Ware protocol, with a direct measurement of oxygen consumption using the gas exchange analyzer (FitMate; Cosmed, Rome, Italy) and concurrent electrocardiogram (12-lead) monitoring.
HbA1c was measured using high-performance liquid chromatography using diabetes control and complications trial-aligned methods; fasting blood glucose, triglycerides, total cholesterol, and HDL cholesterol were determined by standard methods; and LDL cholesterol was calculated by the Friedwald formula.
The elbow flexors (EF) and knee extensors (KE) muscle groups were evaluated because they are relevant for the activities of daily living. Moreover, elbow flexion and knee extension allow to explore a wide range of contraction velocities without interferences due to the difficulty of performing the exercise task.
On the morning of testing, 3 h after a standard breakfast, subjects were requested to perform the following two tests on the ergometer: isometric and isokinetic concentric MVCs. In the isometric test, the elbow angle was fixed at 90° with the upper arm parallel to the trunk and the forearm in a neutral position (halfway between pronation and supination). Also, the knee joint was set at a 90° angle, as the hip joint. The task consisted of rapidly increasing the force exerted by the EF or the KE to a maximum. All subjects were verbally encouraged to produce a maximal contraction and to maintain it for at least 2–3 s before relaxing. A minimum of three maximal attempts were performed separated by 4 min to recover from fatigue. Participants were asked to perform further attempts if the MVC of their last trial exceeded that of the previous trials by at least 10%. However, the number of MVC attempts never exceeded four per subject. In the isokinetic concentric test, the angular velocity values were fixed at 15°, 30°, 60°, 120°, 180°, and 240°·s−1, and subjects were requested to flex the elbow or to extend the knee as strong as possible. The range of motions for elbow flexion and knee extension was 40°–130° and 80°–170°, respectively. The order of the trials was randomized to minimize the effect of skill acquisition. Each contraction was followed by a 4-min rest to prevent cumulative fatigue. In each trial, strong verbal encouragement was given by the test leader.
During the tests, mechanical and electrical recordings were performed simultaneously to derive the torque–angular velocity relationship and MFCV, respectively. For mechanical recordings, the elbow flexion and knee extension torques of the dominant limb were measured with a dynamometer (Kin-Com, Chattanooga, TN). For electrical recordings, sEMG signals were registered with a linear array of four electrodes (silver bars 5 mm long, 1 mm thick, and 10 mm apart; LISiN, Turin, Italy) from the biceps brachii (BB) and the vastus lateralis (VL) muscles. After gentle skin abrasion and cleaning with ethyl alcohol, electrodes were attached on the skin over the BB along the line connecting the acromion to the cubital fossa and over the VL on the line from the anterior spina iliaca superior to the lateral side of the patella. The optimal position and orientation of the electrodes were determined to be conveniently distant from the innervation zone and the tendon as previously described (9). Three sEMG were detected in a single-differential mode. Two double differentials were computed off-line and were used for further analysis. Signals were amplified (×1000), band-pass filtered (10–450 Hz) (EMG 16; LISiN), sampled at 2048 Hz with 12-bit resolution (amplitude range, ±10 V) (DAQ card AI-16XE-50; National Instruments, Austin, TX), recorded, and stored on a personal computer. Skinfolds in the upper and lower limb and at the sites of sEMG electrodes placement were preliminarily assessed by plicometry to rule out influence of this potential confounder on sEMG recordings.
For each MVC task, the repetition that showed the highest value of torque was used for mechanical and sEMG analysis. Peak torques assessed during isometric and isokinetic contractions were used to assess the torque–velocity relationship. Maximal CV was estimated at more than 250-ms windows. CV was estimated from the two double differentials using the cross-correlation technique (Fig. 1). This technique was used to estimate the time delay between the two signals (i.e., the amount of time shift that must be applied to one signal to minimize the mean square error with the other). This time shift is that which maximizes the cross correlation between the signals. Estimates of CV were accepted only when cross-correlation values were higher than 0.8.
Data are expressed as mean ± SD, for continuous variables, and number of cases and percentages for categorical variables. The Kruskal–Wallis one-way ANOVA was applied to compare neurological, clinical, and biochemical data among study groups, whereas the Mann–Whitney test was used for group comparisons. One-way ANOVA was used to detect differences in the torque–velocity relationship in the two limbs (between factors: group; within factor: angular velocity). When indicated, the Tukey post hoc test for multiple comparisons was applied. Regression lines for individual data sets of torque versus angular velocity were computed using the least-squares method. P < 0.05 was considered significant.
Peroneal distal latencies were higher and MNCVs were lower in D1 than that in D4 subjects, according to selection criteria, and these differences were statistically significant. Likewise, VPT was higher and autonomic test values were lower (although not significantly, except for deep breathing test) in D1 versus D4 individuals (Table 1). However, only seven subjects belonging to the D1 group showed a pathological VPT value according to age, whereas only one of them showed alterations of two autonomic tests, as required for diagnosing autonomic neuropathy. Both somatic and autonomic nerve function values were in the normal range in TD and C subjects (Table 1).
Clinical and biochemical parameters
No significant differences were detected among groups in clinical and biochemical parameters, except for HbA1c and fasting blood glucose levels, which were higher in the diabetic groups, and V˙O2max, which was higher in TD individuals, as expected (Table 2). Diabetic subjects assigned to D1, D4, and TD groups did not differ for any of the measured parameters, except for HbA1c, which was higher (P = 0.01) in D1 versus DT, but not versus D4.
Torque during maximal isometric contractions of the EF was similar among groups (Fig. 2A). No significant differences were observed also for the KE in the untrained subjects, although a greater isometric torque was observed in the KE of TD subjects as compared with D1 but not D4 patients (Fig. 2B). A significant interaction was found between angular velocity and groups for both the EF (P = 0.01) and the KE (P < 0.01). With increasing angular velocity, muscle torque recorded at the EF declined, with similar values observed in all groups up to 60°·s−1; in contrast, at 120°, 180°, and 240°·s−1, as compared with the C group, EF torque was significantly lower in D1 and D4, with no difference between these two sedentary diabetic groups (Fig. 2A). Dynamic KE strength was lower in the two diabetic sedentary groups compared with the C group at all angular velocities considered (Fig. 2B), with a difference of −40% between D1 and C groups for angular velocities of >60°·s−1. As compared with D4, D1 showed a similar KE strength at 240°·s−1, whereas it was significantly lower at the intermediate velocities of 60°, 90°, and 120°·s−1. At variance with the two sedentary diabetic groups, KE strength in the TD group was similar to that recorded in the C group, especially at lower angular velocities.
The MFCV of the BB muscle was similar among groups (Fig. 3A). In contrast, MFCV recorded in the VL muscle was lower in both D1 (−23%; P = 0.01) and D4 (−23%, P = 0.01) subjects compared with the nondiabetic C group, whereas it was not significantly different between the TD and the C groups (Fig. 3B). MFCV was significantly lower in VL compared with BB in all groups (P < 0.05).
To the best of our knowledge, this is the first study evaluating isometric and isokinetic strength of the upper and lower limb muscles in patients with diabetes at different contraction velocities with concurrent assessment of the torque–velocity relationship and MFCV. This approach allowed us to characterize the neuromuscular defect associated with diabetes and to gain further insight into the role of motor nerve impairment as a contributing factor and also into the potential of exercise training as a preventive and/or therapeutic measure. In fact, diabetes-induced impairment of muscle strength and the effect of DPN and training status were found to be strongly dependent on whether muscle contraction was performed under isometric or isokinetic conditions and particularly on the contraction velocity, thus implying an effect on muscle power.
The observations that both EF and KE strength were similar among groups under isometric conditions, but differed significantly during shortening contractions at different angular speeds, strongly support the need for exploring various contraction modalities and velocities to investigate neuromuscular function in diabetes. Indeed, isometric and isokinetic conditions are characterized by differences in motor unit recruitment (37), and isometric EF strength may not reflect dynamic muscular performance (38). Our data indicate that dynamic contractions and higher angular velocities may be superior to static contractions to reveal diabetes-related strength deficits.
Our finding that isometric strength was not different in diabetic individuals, independent of motor nerve impairment and training status, is difficult to reconcile with previous studies showing a reduced handgrip (13,29,34) and lower leg (21,22) strength in diabetic subjects, although a longitudinal study reported no difference in handgrip strength between diabetic and control subjects (30). The observation that, under dynamic conditions, EF strength was lower in sedentary patients with diabetes than that in control subjects only at velocities ≥120°·s−1 is consistent with a previous report showing a conserved EF strength at 60°·s−1 in patients with diabetes (1). In addition, this finding confirms that the upper limb muscle strength is also impaired in diabetic individuals (13,29,34), although to a lesser extent than the lower limb, thus suggesting that factors other than DPN are involved in diabetes-induced neuromuscular dysfunction. More importantly, it indicates for the first time that the effect of diabetes on muscle function in the arm is more pronounced in dynamic than that in static conditions and at higher movement velocities. Our results are consistent with previous studies testing KE isokinetic strength at single angular velocities in cross-sectional (1–3,29) and longitudinal (30) design and reporting lower values in sedentary patients with diabetes than that in control subjects. However, our data add the important information that the detrimental effect of diabetes on KE muscle strength is present for a wide range of contraction velocities and is more pronounced in dynamic than that in static conditions. This has important practical implications, as a reduction in KE power has been shown to occur in mobility-limited older adults (15) and to predict performance during functional tasks in these individuals (8), thus suggesting that the downward shift of the torque–velocity relationship in patients with diabetes and the resulting reduction in muscle power is similar to the known effect of aging (32).
In our study, muscle strength under isometric conditions did not differ significantly between patients with diabetes in the lower and the higher quartile of MNCV, in agreement with previous investigations testing KE strength (21,22). Again, a significant difference emerged under dynamic conditions, with a greater KE, but not EF strength deficit in D1 than that in D4 subjects at low to intermediate but not high contraction velocities. These data are consistent with previous reports of a reduced lower leg isokinetic strength in subjects with DPN (1–5), which has been linked to denervation, partial reinnervation (3), and progressive atrophy of skeletal muscle (5). On the other hand, our findings indicate that DPN is only a contributing factor for lower limb muscle weakness, with other mechanisms being implicated in muscle dysfunction at both the upper and the lower limb level. In addition, these data show that also the detrimental effect of motor nerve impairment on dynamic muscle strength in diabetic subjects is dependent on contraction velocity, thus further supporting the importance of testing patients at different angular speeds.
Long-term exercise training was not associated with a greater EF strength, at all velocities considered. Conversely, KE strength in TD patients was greater than that observed in their sedentary counterparts and similar to that detected in controls, under both isometric and dynamic conditions. The larger group difference observed in the KE of TD and D individuals might be related to differences in strength defect or response to training between the EF and the KE, whereas the lower effect of training status at higher than lower angular velocities could be related to differences in the characteristics of the training protocols for the arm and the leg. Longitudinal training studies should be conducted to elucidate the specific functional responses to exercise and their mechanistic basis in neural and/or muscular factors. Of note, and in analogy with what proposed for older individuals (32), the present data point to the importance of considering contraction velocity when planning exercise training protocols for patients with diabetes. More specifically, a higher volume of activity to the lower extremities and a higher speed of movement in the exercises should be considered.
The propagation velocity of the action potential along the muscle fibers during isometric MCVs was lower in patients with diabetes in the lower but not in the upper limb, in keeping with previous studies assessing MFCV during electrically stimulated contractions of the tibialis anterior muscle by the use of invasive techniques (14,26). Although the significant between-group differences in MFCVs in the VL but not in the BB muscle might be explained by the typical pattern of distribution of DPN, the similar MFCVs recorded in the leg of diabetic subjects with lower and higher MNCVs suggest that diabetes-induced reduction in MFCV is an early phenomenon occurring independently of motor nerve dysfunction and possibly linked to changes in the functional characteristics of muscle fibers, in keeping with the report of a reduced muscle quality in diabetic subjects (29,30). In addition, the finding that the MFCV values in TD patients were higher than those of their sedentary counterparts and similar to those of control subjects suggests that MFCV might be a sensitive and noninvasive marker of exercise-induced improvement in neuromuscular function in diabetes.
MFCV is influenced by several factors, including sarcolemmal properties and fiber diameter and type, which might have played a central role in the alterations observed in this study. Sarcolemmal excitability, which is regulated by ion channels, is critical for skeletal muscle function (23). Studies in diabetic animals showed reduced membrane potential, increased membrane resistance, and prolonged duration of the action potential (20), associated with sarcolemmal ion channels abnormalities (25). Thus, alterations of membrane integrity might explain the lower MFCV values observed in the leg. Conversely, the restoration of MFCV in the VL of TD patients might reflect, at least partly, the muscle hypertrophy resulting from regular exercise. However, we cannot exclude that a change in muscle performance might have resulted also from a shift in muscle fiber type composition associated with diabetes (18,28), although the functional characteristics of a muscle can change also by virtue of adaptations in muscle fiber contractile properties without changes in myosin isoform content (12). Studies in diabetic rodents showed a more marked strength loss in fast-twitch muscles (17,24,31) and in skinned fast-twitch single fibers (31,33) than that in slow-twitch muscles. In addition, a prolongation of the twitch response in slow muscles and fibers has been reported in diabetic animals (17,31,36), and a significant reduction in ATPase activity, a marker of muscle contractility, has been found in both type 1 and type 2 muscle fibers of diabetic humans (28). Thus, a defect of the fast characteristics in the diabetic muscle would support the shift in the torque–velocity relationship observed in sedentary patients with diabetes, both in the arm and in the leg.
In conclusion, these data indicate a detrimental effect of diabetes on the relationship between muscle torque and angular velocity. This defect is more pronounced in the leg than that in the arm, is more evident under dynamic than isometric conditions, is strongly dependent on contraction velocity, and is only partly related to motor nerve impairment. Changes in muscle fiber contractile properties with the reduction of MFCV may contribute to diabetes-induced neuromuscular impairment. MFCV and muscle strength deficits are counteracted by exercise training, although the extent of the beneficial effect on strength appears to be less pronounced at higher contraction velocities. This highlights the need for structure-specific exercise programs.
This work was supported by the University of Rome “ForoItalico” (grant life09) and the Metabolic Fitness Association.
The authors declare no conflict of interest.
The results of this study do not constitute endorsement by the American College of Sports Medicine.
1. Andersen H, Nielsen S, Mogensen CE, Jakobsen J. Muscle strength in type 2 diabetes. Diabetes
. 2004; 53: 1543–8.
2. Andersen H, Poulsen PL, Mogensen CE, Jakobsen J. Isokinetic muscle strength in long-term IDDM patients in relation to diabetic complications. Diabetes
. 1996; 45: 440–5.
3. Andersen H, Stalberg E, Gjerstad MD, Jakobsen J. Association of muscle strength and electrophysiological measures of reinnervation in diabetic neuropathy. Muscle Nerve
. 1998; 21: 1647–54.
4. Andreassen CS, Jakobsen J, Andersen H. Muscle weakness: a progressive late complication in diabetic distal symmetric polyneuropathy. Diabetes
. 2006; 55: 806–12.
5. Andreassen CS, Jakobsen J, Ringgaard S, Ejskjaer N, Andersen H. Accelerated atrophy of lower leg and foot muscles—a follow-up study of long-term diabetic polyneuropathy using magnetic resonance imaging (MRI). Diabetologia
. 2009; 52: 1182–91.
6. Balducci S, Iacobellis G, Parisi L, et al.. Exercise training can modify the natural history of diabetic peripheral neuropathy. J Diabetes Complications
. 2006; 20: 216–23.
7. Balducci S, Zanuso S, Nicolucci A, et al.. Effect of an intensive exercise intervention strategy on modifiable cardiovascular risk factors in subjects with type 2 diabetes mellitus: a randomized controlled trial: the Italian Diabetes and Exercise Study (IDES). Arch Intern Med
. 170 (20): 1794–803.
8. Bassey EJ, Fiatarone MA, O’Neill EF, Kelly M, Evans WJ, Lipsitz LA. Leg extensor power and functional performance in very old men and women. Clin Sci (Lond)
. 1992; 82: 321–7.
9. Bazzucchi I, Felici F, Macaluso A, De Vito G. Differences between young and older women in maximal force, force fluctuations, and surface EMG during isometric knee extension and elbow flexion. Muscle Nerve
. 2004; 30: 626–35.
10. Caiozzo VJ. Plasticity of skeletal muscle phenotype: mechanical consequences. Muscle Nerve
. 2002; 26: 740–68.
11. Cameron NE, Cotter MA, Robertson S. Changes in skeletal muscle contractile properties in streptozocin-induced diabetic rats and role of polyol pathway and hypoinsulinemia. Diabetes
. 1990; 39: 460–5.
12. Canepari M, Pellegrino MA, D’Antona G, Bottinelli R. Skeletal muscle fibre diversity and the underlying mechanisms. Acta Physiol (Oxf)
. 2010; 199: 465–76.
13. Cetinus E, Buyukbese MA, Uzel M, Ekerbicer H, Karaoguz A. Hand grip strength in patients with type 2 diabetes mellitus. Diabetes Res Clin Pract
. 2005; 70: 278–86.
14. Chisari C, Piaggesi A, Baccetti F, Licitra R, Rossi B. Muscle modification in asymptomatic diabetic neuropathy: a surface electromyographic study. Basic Appl Myol
. 2002; 12: 177–81.
15. Clark DJ, Patten C, Reid KF, Carabello RJ, Phillips EM, Fielding RA. Impaired voluntary neuromuscular activation limits muscle power in mobility-limited older adults. J Gerontol A Biol Sci Med Sci
. 2010; 65: 495–502.
16. Colberg SR, Sigal RJ, Fernhall B, et al.. Exercise and type 2 diabetes: the American College of Sports Medicine and the American Diabetes Association: joint position statement executive summary. Diabetes Care
. 2010; 33: 2692–6.
17. Cotter M, Cameron NE, Lean DR, Robertson S. Effects of long-term streptozotocin diabetes on the contractile and histochemical properties of rat muscles. Q J Exp Physiol
. 1989; 74: 65–74.
18. Gaster M, Staehr P, Beck-Nielsen H, Schroder HD, Handberg A. GLUT4 is reduced in slow muscle fibers of type 2 diabetic patients: is insulin resistance in type 2 diabetes a slow, type 1 fiber disease? Diabetes
. 2001; 50: 1324–9.
19. Gregg EW, Beckles GL, Williamson DF, et al.. Diabetes and physical disability among older U.S. adults. Diabetes Care
. 2000; 23: 1272–7.
20. Grossie J. Contractile and electrical characteristics of extensor muscle from alloxan-diabetic rats. An in vitro study. Diabetes
. 1982; 31: 194–202.
21. Ijzerman TH, Schaper NC, Melai T, et al.. Motor nerve decline does not underlie muscle weakness in type 2 diabetic neuropathy. Muscle Nerve
. 2011; 44: 241–5.
22. Ijzerman TH, Schaper NC, Melai T, Meijer K, Willems PJ, Savelberg HH. Lower extremity muscle strength is reduced in people with type 2 diabetes, with and without polyneuropathy, and is associated with impaired mobility and reduced quality of life. Diabetes Res Clin Pract
. 2012; 95: 345–51.
23. Jurkat-Rott K, Holzherr B, Fauler M, Lehmann-Horn F. Sodium channelopathies of skeletal muscle result from gain or loss of function. Pflugers Arch
. 460: 239–48.
24. Lesniewski LA, Miller TA, Armstrong RB. Mechanisms of force loss in diabetic mouse skeletal muscle. Muscle Nerve
. 2003; 28: 493–500.
25. Lin-Shiau SY, Liu SH, Lin MJ. Use of ion channel blockers in the exploration of possible mechanisms involved in the myopathy of diabetic mice. Naunyn Schmiedebergs Arch Pharmacol
. 1993; 348: 311–8.
26. Meijer JW, Lange F, Links TP, van der Hoeven JH. Muscle fiber conduction abnormalities in early diabetic polyneuropathy. Clin Neurophysiol
. 2008; 119: 1379–84.
27. Merletti R, Farina D, Gazzoni M. The linear electrode array: a useful tool with many applications. J Electromyogr Kinesiol
. 2003; 13: 37–47.
28. Oberbach A, Bossenz Y, Lehmann S, et al.. Altered fiber distribution and fiber-specific glycolytic and oxidative enzyme activity in skeletal muscle of patients with type 2 diabetes. Diabetes Care
. 2006; 29: 895–900.
29. Park SW, Goodpaster BH, Strotmeyer ES, et al.. Decreased muscle strength and quality in older adults with type 2 diabetes: the health, aging, and body composition study. Diabetes
. 2006; 55: 1813–8.
30. Park SW, Goodpaster BH, Strotmeyer ES, et al.. Accelerated loss of skeletal muscle strength in older adults with type 2 diabetes: the health, aging, and body composition study. Diabetes Care
. 2007; 30: 1507–12.
31. Paulus SF, Grossie J. Skeletal muscle in alloxan diabetes. A comparison of isometric contractions in fast and slow muscle. Diabetes
. 1983; 32: 1035–9.
32. Raj IS, Bird SR, Shield AJ. Aging and the force–velocity relationship of muscles. Exp Gerontol
. 45: 81–90.
33. Sanchez OA, Snow LM, Lowe DA, Serfass RC, Thompson LV. Effects of endurance exercise-training on single-fiber contractile properties of insulin-treated streptozotocin-induced diabetic rats. J Appl Physiol
. 2005; 99: 472–8.
34. Sayer AA, Dennison EM, Syddall HE, Gilbody HJ, Phillips DI, Cooper C. Type 2 diabetes, muscle strength, and impaired physical function: the tip of the iceberg? Diabetes Care
. 2005; 28: 2541–2.
35. Stenholm S, Harkanen T, Sainio P, Heliovaara M, Koskinen S. Long-term changes in handgrip strength in men and women—accounting the effect of right censoring due to death. J Gerontol A Biol Sci Med Sci
. 2012; 67 (10): 1068–74.
36. Stephenson GM, O’Callaghan A, Stephenson DG. Single-fiber study of contractile and biochemical properties of skeletal muscles in streptozotocin-induced diabetic rats. Diabetes
. 1994; 43: 622–8.
37. Tax AA, Denier van der Gon JJ, Gielen CC, van den Tempel CM. Differences in the activation of m. biceps brachii in the control of slow isotonic movements and isometric contractions. Exp Brain Res
. 1989; 76: 55–63.
38. van Bolhuis BM, Medendorp WP, Gielen CC. Motor unit firing behavior in human arm flexor muscles during sinusoidal isometric contractions and movements. Exp Brain Res
. 1997; 117: 120–30.
39. Zanuso S, Jimenez A, Pugliese G, Corigliano G, Balducci S. Exercise for the management of type 2 diabetes: a review of the evidence. Acta Diabetol
. 2009; 47: 15–22.
40. Zwarts MJ, Stegeman DF. Multichannel surface EMG: basic aspects and clinical utility. Muscle Nerve
. 2003; 28: 1–17.
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©2013The American College of Sports Medicine
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